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Semantic Segmentation

847 papers with code · Computer Vision

Semantic segmentation, or image segmentation, is the task of clustering parts of an image together which belong to the same object class. It is a form of pixel-level prediction because each pixel in an image is classified according to a category.

Some example benchmarks for this task are Cityscapes, PASCAL VOC and ADE20K. Models are usually evaluated with the Mean Intersection-Over-Union (Mean IoU) and Pixel Accuracy metrics.

( Image credit: CSAILVision )

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Latest papers with code

PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

31 Mar 2020edwardzhou130/PolarSeg

The requirement of fine-grained perception by autonomous driving systems has resulted in recently increased research in the online semantic segmentation of single-scan LiDAR.

AUTONOMOUS DRIVING SEMANTIC SEGMENTATION

32
31 Mar 2020

Probabilistic Pixel-Adaptive Refinement Networks

31 Mar 2020visinf/ppac_refinement

Encoder-decoder networks have found widespread use in various dense prediction tasks.

OPTICAL FLOW ESTIMATION SEMANTIC SEGMENTATION

22
31 Mar 2020

DISIR: Deep Image Segmentation with Interactive Refinement

31 Mar 2020delair-ai/DISIR

Starting from an initial output based on the image only, our network then interactively refines this segmentation map using a concatenation of the image and user annotations.

SEMANTIC SEGMENTATION

9
31 Mar 2020

Generalizable Semantic Segmentation via Model-agnostic Learning and Target-specific Normalization

27 Mar 2020koncle/TSMLDG

To overcome this limitation, we propose a novel domain generalization framework for the generalizable semantic segmentation task, which enhances the generalization ability of the model from two different views, including the training paradigm and the data-distribution discrepancy.

DOMAIN GENERALIZATION SEMANTIC SEGMENTATION

4
27 Mar 2020

What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective

25 Mar 2020ZhangLi-CS/GCP_Optimization

Recent works have demonstrated that global covariance pooling (GCP) has the ability to improve performance of deep convolutional neural networks (CNNs) on visual classification task.

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

10
25 Mar 2020

Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection

24 Mar 2020yuliangguo/3D_Lane_Synthetic_Dataset

The method, inspired by the latest state-of-the-art 3D-LaneNet, is a unified framework solving image encoding, spatial transform of features and 3D lane prediction in a single network.

LANE DETECTION SEMANTIC SEGMENTATION

18
24 Mar 2020

SOLOv2: Dynamic, Faster and Stronger

23 Mar 2020aim-uofa/AdelaiDet

Importantly, we take one step further by dynamically learning the mask head of the object segmenter such that the mask head is conditioned on the location.

INSTANCE SEGMENTATION OBJECT DETECTION PANOPTIC SEGMENTATION

485
23 Mar 2020

Learning Dynamic Routing for Semantic Segmentation

23 Mar 2020yanwei-li/DynamicRouting

To demonstrate the superiority of the dynamic property, we compare with several static architectures, which can be modeled as special cases in the routing space.

SEMANTIC SEGMENTATION

109
23 Mar 2020

CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection

20 Mar 2020KiveeDong/CentripetalNet

CentripetalNet predicts the position and the centripetal shift of the corner points and matches corners whose shifted results are aligned.

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

91
20 Mar 2020

Collaborative Video Object Segmentation by Foreground-Background Integration

18 Mar 2020z-x-yang/CFBI

With the feature embedding from both foreground and background, our CFBI performs the matching process between the reference and the predicted sequence from both pixel and instance levels, making the CFBI be robust to various object scales.

SEMANTIC SEGMENTATION SEMI-SUPERVISED VIDEO OBJECT SEGMENTATION VIDEO SEMANTIC SEGMENTATION

6
18 Mar 2020